ABSTRACT
Membrane fouling is a critical bottleneck to the widespread adoption of membrane separation processes. It diminishes the membrane permeability and results in high operational energy costs. The current study presents optimizing the operating parameters of a novel rotating biological contactor (RBC) integrated with an external membrane (RBC + ME) that combines membrane technology with an RBC. In the RBC + ME, the membrane panel is placed external to the bioreactor. Response surface methodology (RSM) is applied to optimize the membrane permeability through three operating parameters (hydraulic retention time (HRT), rotational disk speed, and sludge retention time (SRT)). The artificial neural networks (ANN) and support vector machine (SVM) are implemented to depict the statistical modelling approach using experimental data sets. The results showed that all three operating parameters contribute significantly to the performance of the bioreactor. RSM revealed an optimum value of 40.7 rpm disk rotational speed, 18 h HRT and 12.4 d SRT, respectively. An ANN model with ten hidden layers provides the highest R2 value, while the SVM model with the Bayesian optimizer provides the highest R2. RSM, ANN, and SVM models reveal the highest R-square values of 0.97, 0.99, and 0.99, respectively. Machine learning techniques help predict the model based on the experimental results and training data sets.
Subject(s)
Neural Networks, Computer , Support Vector Machine , Bayes Theorem , Bioreactors , SewageABSTRACT
Presently, composite membranes emerged as a promising approach to overcome the limitations of polymeric and inorganic membranes particularly in acid gas separation. In the present work, composites membranes were fabricated by combining hierarchical T-Type (h-zeolite T) zeolite and PEBA-1657 at different filler composition that ranging from 5 wt% - 30 wt% for the CO2/CH4 separation. The physicochemical properties of the resultant inorganic filler and membranes were investigated by using Brunauer-Emmett- Teller (BET), field emission scanning electron microscopy (FESEM), Fourier Transform infra-red (FTIR), x-ray diffraction (XRD), thermogravimetric analysis (TGA) and differential scanning calorimetry (DSC). FESEM and EDX analysis revealed that the formation of voids and agglomeration of particles is pronounced as the fillers loading was increased up to 30 wt%. The single gas permeation test demonstrated that amalgamation of h-zeolite T particles into PEBA-1657 has resulted in the improvement of CO2 permeability up to 122% and CO2/CH4 selectivity up to 31%. Hybrid membrane encapsulated with 25 wt% of h-zeolite T displayed a maximum separation efficiency with the highest CO2 permeability of 164.83 Barrer and CO2/CH4 selectivity of 19.37. However, further increment of fillers composition up to 30 wt% resulted in a sharp reduction of CO2/CH4 selectivity to 15.80 due to the particles sedimentation and agglomeration. Overall, the favorable gas transport behavior of PEBA-1657/h-zeolite T composite membrane indicates its promising prospect for CO2/CH4 separation especially in biogas and natural gas purification application. Future research efforts are directed on the optimization of the fabrication parameters and performance investigation at different operating condition to further enhance the CO2 separation and extend its operability under various environment.
